Data Sources: The Oscar Award, 1927-2025 (acquired from Kaggle), Film and Actor Details (acquired from The Movie Database API), Google Trends
Three Most Popular Months for Google Search Interest by Actor Type
Type Month Google Trend Search Interest (mean)
Commercially Successful 1 13.1
Commercially Successful 7 13.1
Commercially Successful 12 12.7
Oscar Nominated 1 12.0
Oscar Nominated 2 11.6
Oscar Nominated 3 11.0
Commercially Successful & Oscar Nominated 1 14.5
Commercially Successful & Oscar Nominated 2 13.4
Commercially Successful & Oscar Nominated 12 13.1
Data Sources: The Oscar Award, 1927-2025 (acquired from Kaggle), Film and Actor Details (acquired from The Movie Database API), Google Trends
Five Most Representative Actors in Each Cluster
1 - Blockbuster Staple 2 - Breakout Star or Memorialized 3 - Critically Acclaimed 4 - Pop Fame 5 - Emerging or Consistent Stardom
Chris Hemsworth Maria Bakalova Felicity Jones Taylor Lautner Gwilym Lee
Nicolas Cage Chadwick Boseman Glen Powell Orlando Bloom Tao Okamoto
Lyna Irrfan Khan Rami Malek Megan Fox George MacKay
Sam Elliott Jean Dujardin Tom Hiddleston Freida Pinto Zazie Beetz
Mads Mikkelsen Carrie Fisher Pedro Pascal Moon Bloodgood Theo James
Data Sources: The Oscar Award, 1927-2025 (acquired from Kaggle), Film and Actor Details (acquired from The Movie Database API), Google Trends
What Percent of Actors in Each Cluster are Oscar Nominees?
Cluster Percent Nominees (%)
1 - Blockbuster Staple 25
2 - Breakout Star or Memorialized 45
3 - Critically Acclaimed 41
4 - Pop Fame 22
5 - Emerging or Consistent Stardom 30
Random Forest Model Comparison
Model 1 - All Predictors Model 2 - Time Series Predictors Only
Number of Trees 500.0000 500.0000
Out-of-Bag Error Rate 0.2411 0.2549
Model Accuracy Comparison
Model 1 - All Predictors Model 2 - Time Series Predictors Only
Accuracy 0.75 0.7266
Evaluation Metrics Comparison
Model 1 - All Predictors Model 2 - Time Series Predictors Only
Precision 0.7353 0.7101
Recall 0.7812 0.7656
F1 Score 0.7576 0.7368
## Model 1 - All Predictors
## Confusion Matrix and Statistics
## 
##           Reference
## Prediction  0  1
##          0 49 20
##          1 15 44
##                                           
##                Accuracy : 0.7266          
##                  95% CI : (0.6408, 0.8016)
##     No Information Rate : 0.5             
##     P-Value [Acc > NIR] : 1.492e-07       
##                                           
##                   Kappa : 0.4531          
##                                           
##  Mcnemar's Test P-Value : 0.499           
##                                           
##             Sensitivity : 0.7656          
##             Specificity : 0.6875          
##          Pos Pred Value : 0.7101          
##          Neg Pred Value : 0.7458          
##              Prevalence : 0.5000          
##          Detection Rate : 0.3828          
##    Detection Prevalence : 0.5391          
##       Balanced Accuracy : 0.7266          
##                                           
##        'Positive' Class : 0               
## 
## Model 2 - Time Series Predictors Only
## Confusion Matrix and Statistics
## 
##           Reference
## Prediction  0  1
##          0 49 20
##          1 15 44
##                                           
##                Accuracy : 0.7266          
##                  95% CI : (0.6408, 0.8016)
##     No Information Rate : 0.5             
##     P-Value [Acc > NIR] : 1.492e-07       
##                                           
##                   Kappa : 0.4531          
##                                           
##  Mcnemar's Test P-Value : 0.499           
##                                           
##             Sensitivity : 0.7656          
##             Specificity : 0.6875          
##          Pos Pred Value : 0.7101          
##          Neg Pred Value : 0.7458          
##              Prevalence : 0.5000          
##          Detection Rate : 0.3828          
##    Detection Prevalence : 0.5391          
##       Balanced Accuracy : 0.7266          
##                                           
##        'Positive' Class : 0               
##